Pipeline for Document Scoring

2. The method of claim 1, wherein performing the operation further comprises assigning, by the document scoring computer system, a rank to a document within the set of search results based upon a document score assigned to the document.

3. The method of claim 2 further comprising displaying, on a display of the document scoring computer system, the set of search results in response to receiving the query, wherein a document is populated within the set of search results based upon the rank.

4. The method of claim 1 further comprising: indexing, by the document scoring computer system, a document based upon a document score exceeding a threshold.

5. The method of claim 1 further comprising: refraining, by the document scoring computer system, from indexing a document based upon a document score not exceeding a threshold.

6. The method of claim 1, wherein the one or more levels of feature sets comprise at least one of page level features joined into a joined page level feature set, domain level features joined into a joined domain level feature set, or host level features joined into a joined host level feature set.

7. The method of claim 1, wherein the document score is indicative of at least one of an importance or quality of the document.

8. The method of claim 1, wherein the document score is indicative of a relevancy of the document.

9. The method of claim 1, wherein a numerical feature corresponds to a numerical statistic of a target document.

10. The method of claim 1, wherein a document comprises a webpage.

11. The method of claim 1, wherein a document comprises a text document.

12. The method of claim 1, wherein a numerical feature corresponds to a number of times a target document is linked to.

13. The method of claim 6, wherein a domain level feature corresponds to a feature of a domain associated with a target document.

14. The method of claim 6, wherein a host level feature corresponds to a feature of a host associated with a target document.

15. The method of claim 1, wherein the machine learning comprises a gradient boosted decision tree regression technique.

16. The method of claim 1 further comprising merging, by the document scoring computer system, the numerical features with the content features for scoring a document using the document scoring model.

17. The method of claim 1, wherein a numerical feature corresponds to a ratio of an amount of a first type of content within a target document to an amount of a second type of content within the target document.

18. The method of claim 1, wherein the content features comprise textual features of a target document.

20. The method of claim 1, wherein performing the operation on the plurality of documents further comprises selectively indexing, by the document scoring computer system, the subset of the documents based upon the document scores of the documents.

21. The computing device of claim 19, wherein the processor is caused to one of perform a ranking of documents in search based on the document scores of the subset of the documents and selectively index the subset of the documents based upon the document scores of the documents.

22. The computing device of claim 19, wherein the machine learning comprises a gradient boosted decision tree regression technique.